6 citations · 14 across the 6 of their papers we have counts for
6 papers
Pretraining Large Language Models with NVFP4
NVIDIA, Felix Abecassis, Anjulie Agrusa +87
Large Language Models (LLMs) today are powerful problem solvers across many domains, and they continue to get stronger as they scale in model size, training set size, and training…
WenyanGPT: A Large Language Model for Classical Chinese Tasks
Xinyu Yao, Mengdi Wang, Bo Chen +1
Classical Chinese, as the core carrier of Chinese culture, plays a crucial role in the inheritance and study of ancient literature. However, existing natural language processing mo…
Long Term Memory: The Foundation of AI Self-Evolution
Xun Jiang, Feng Li, Han Zhao +12
Large language models (LLMs) like GPTs, trained on vast datasets, have demonstrated impressive capabilities in language understanding, reasoning, and planning, achieving human-leve…
Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules
Joseph C. Kim, David Bloore, Karan Kapoor +3
The Boltzmann distribution of a protein provides a roadmap to all of its functional states. Normalizing flows are a promising tool for modeling this distribution, but current metho…
Voting-Based Multi-Agent Reinforcement Learning for Intelligent IoT
Yue Xu, Zengde Deng, Mengdi Wang +3
The recent success of single-agent reinforcement learning (RL) in Internet of things (IoT) systems motivates the study of multi-agent reinforcement learning (MARL), which is more c…
RL4health: Crowdsourcing Reinforcement Learning for Knee Replacement Pathway Optimization
Hao Lu, Mengdi Wang
Joint replacement is the most common inpatient surgical treatment in the US. We investigate the clinical pathway optimization for knee replacement, which is a sequential decision p…